Document and data intelligence
Turn mixed information into records you can use.
We build systems that turn PDFs, emails, photographs, spreadsheets, O&M manuals and scanned records into structured, searchable and usable data. They are for organisations whose important information is spread across documents and incomplete databases rather than one clean system.
Discuss a workflowThe problem
Mixed formats
Key facts sit inside PDFs, tables, images and messages that no system can query.
Incomplete records
Databases have gaps, duplicates and inconsistent values that undermine reporting.
Manual re-keying
Staff copy the same information between documents and systems, introducing delay and error.
What we build
Most organisations do not have a clean data problem. They have a mixed-information problem. We turn that material into structured records.
- Extract key fields from documents, tables, messages and images
- Classify records and assign confidence
- Enrich incomplete records with approved reference data
- Identify duplicates, inconsistencies, omissions and unusual values
- Link related evidence across locations and systems
- Prepare management views, reports and downstream actions
How it connects to compliance
Compliance depends on finding the right record and proving where it came from. The same extraction, classification and linking described here is the foundation of our compliance and evidence systems, where each record is associated with the obligation it supports.
Explore compliance systems →Applied proof
Emergency-lighting compliance workflow
EGG operates a managed workflow that extracts recurring test information, identifies faults, logs remediation and produces scheduled reports and annual certification as one continuous record.
See the compliance approach →Compliance evidence engine
Ingests selected SharePoint and local folders and maintains an audit log. Classification, evidence links and gap monitoring remain development work.
Frequently asked questions
What kinds of documents can you work with?
PDFs, scanned records, spreadsheets, emails, photographs and manuals. Each implementation is tested on a sample of your real material.
How accurate is the extraction?
Every result carries a confidence level, and low-confidence items are routed for human review rather than accepted silently.
Does our data leave our systems?
Data sources, access and processing locations are agreed during design, and access is restricted to selected sources.
Can the output feed our existing systems?
Yes. Structured records can be exported or pushed to existing systems through APIs where they are available.
Bring us one pile of documents you wish you could query.
We will tell you where AI is useful, what should remain rule-based and what a practical first build would look like.
No transformation programme required. Start with one process.